Improving small area estimation by combining surveys: new perspectives in regional statistics.
A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devise...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2006 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3785 |
| Acceso en línea: | https://hdl.handle.net/2099/3785 |
| Access Level: | acceso abierto |
| Palabra clave: | Inference Multivariate analysis Inferència Anàlisi multivariable Classificació AMS::62 Statistics::62J Linear inference, regression Classificació AMS::62 Statistics::62H Multivariate analysis |
| Sumario: | A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study. |
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